1. Field of the Invention
The present invention relates techniques for automatically annotating images. More specifically, the present invention relates a technique that automatically annotates an image by searching for similar images and correlating text surrounding these similar images.
2. Related Art
The recent proliferation of high-bandwidth Internet connections presently makes it possible for millions of users to efficiently view images on the Internet. These developments have led to a tremendous increase in the number of images that are incorporated into web pages, web portals, and other web-based applications. Unfortunately, many images do not come with accompanying textual information, such as labels, captions, or titles, to describe the content of the images. This makes it extremely difficult to search for specific images because most existing search techniques are text based (e.g., a keyword search). Hence, it is highly desirable to annotate such images with relevant text, for example, by adding a set of keywords or a caption to describe the semantic content of an image.
Traditional techniques for annotating images are primarily manual, which can require human indexers to select keywords for thousands or, in some cases, millions of images. Hence, manual image annotation can be an extremely labor-intensive and expensive procedure.
Other techniques have been developed to automatically annotate an image (see “Formulating Semantic Image Annotation as a Supervised Learning Problem,” G. Carneiro and N. Vasconcelos, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Diego, 2005). These automatic image-annotation techniques can significantly reduce or eliminate the human effort required to annotate very large image collections.
However, these existing “automatic annotation” techniques typically still involve steps that require some degree of human assistance, such as requiring manual labeling of a set of ground truth data, or by requiring other types of human interaction or feedback. Unfortunately, this human assistance cannot be efficiently scaled to match the exponentially growing number of images which need to be annotated.
Hence, what is need is a method and an apparatus for automatically annotating an image without the above-described problems.